[6416] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[9456] | 3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6416] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System.Collections.Generic;
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| 23 | using HeuristicLab.Data;
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| 24 | using HeuristicLab.Encodings.PermutationEncoding;
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| 25 |
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| 26 | namespace HeuristicLab.Problems.QuadraticAssignment {
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| 27 | public static class QAPPermutationProximityCalculator {
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| 28 |
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| 29 | public static double CalculateGenotypeSimilarity(Permutation a, Permutation b) {
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| 30 | int similar = 0;
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| 31 | for (int i = 0; i < a.Length; i++) {
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| 32 | if (a[i] == b[i]) similar++;
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| 33 | }
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| 34 | return similar / (double)a.Length;
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| 35 | }
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| 36 |
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| 37 | public static double CalculateGenotypeDistance(Permutation a, Permutation b) {
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| 38 | return 1.0 - CalculateGenotypeSimilarity(a, b);
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| 39 | }
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| 40 |
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| 41 | public static double CalculatePhenotypeSimilarity(Permutation a, Permutation b, DoubleMatrix weights, DoubleMatrix distances) {
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| 42 | return 1.0 - CalculatePhenotypeDistance(a, b, weights, distances);
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| 43 | }
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| 44 |
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| 45 | public static double CalculatePhenotypeDistance(Permutation a, Permutation b, DoubleMatrix weights, DoubleMatrix distances) {
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[6627] | 46 | Dictionary<double, Dictionary<double, int>> alleles = new Dictionary<double, Dictionary<double, int>>();
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| 47 | int distance = 0, len = a.Length;
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| 48 | for (int x = 0; x < len; x++) {
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| 49 | for (int y = 0; y < len; y++) {
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| 50 | // there's a limited universe of double values as they're all drawn from the same matrix
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| 51 | double dA = distances[a[x], a[y]], dB = distances[b[x], b[y]];
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| 52 | if (dA == dB) continue;
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[6416] | 53 |
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[6627] | 54 | Dictionary<double, int> dAlleles;
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| 55 | if (!alleles.ContainsKey(weights[x, y])) {
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| 56 | dAlleles = new Dictionary<double, int>();
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| 57 | alleles.Add(weights[x, y], dAlleles);
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| 58 | } else dAlleles = alleles[weights[x, y]];
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| 59 |
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[6416] | 60 | int countA = 1, countB = -1;
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| 61 |
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[6627] | 62 | if (dAlleles.ContainsKey(dA)) countA += dAlleles[dA];
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| 63 | if (dAlleles.ContainsKey(dB)) countB += dAlleles[dB];
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| 64 |
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[6416] | 65 | if (countA <= 0) distance--; // we've found in A an allele that was present in B
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| 66 | else distance++; // we've found in A a new allele
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[6627] | 67 | dAlleles[dA] = countA;
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[6416] | 68 |
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| 69 | if (countB >= 0) distance--; // we've found in B an allele that was present in A
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| 70 | else distance++; // we've found in B a new allele
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[6627] | 71 | dAlleles[dB] = countB;
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[6416] | 72 | }
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| 73 | }
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[6627] | 74 | return distance / (double)(2 * len * len);
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[6416] | 75 | }
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| 76 | }
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| 77 | }
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